Questions tagged [sensitivity-analysis]

Auxiliary methods intended to check if the outcome of an analysis strongly depends on the model assumptions, preprocessing steps, presence of outliers, etc.

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Survival (Kamplan-Meier) sensitivity analysis

I conducted a Kaplan-Meier survival analysis to compare survival of 4 groups. The log-rank test yielded a p-value of <0.05. When I conduct pairwise comparisons of the 4 groups (adjusted for ...
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A few queries regarding Meta-analysis and its subparts using R

As part of a meta-analysis of a disease in R, I received some feedback on the paper of which it is a part by external consultants. I cannot contact them again, and am confused about the advice they ...
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Understanding "In Bayesian inference, the difference between data and a parameter is that one is observed (data) and one isn't (parameter)" [duplicate]

In his statistical rethinking course, Richard Mclreath states "In Bayesian inference, the difference between data and a parameter is that one is observed (data) and one isn't (parameter)" I ...
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Inferring effect & effect modification from simulation data

I have a "black box" system (computer simulation), which takes inputs: $x_1 \in [0,1]$, $x_2 \in [0,1]$, and $N_i$ others $\vec\theta = \{\theta_1, \dots, \theta_{N_i}\}$, and produces an ...
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When do we do sensitivity analysis in biostat and how do we do it?

I have two questions below. I have seen people doing sensitivity analysis in observational study papers for the model to check sensitivity to assumptions in bayesian context for selection of priors. I ...
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how perform sensitivity analysis in R?

I have a question about the multinomial logit model in R, I fitted a model and now I want to do sensitivity analysis, consider this equation for example, V1 = ASC1 +a1×Inc+b1×HS+c1×Cld+e1×Dri+ f1×Edu+ ...
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Which R package should be used to perform sensitivity analysis for multi criterion decision making models?

I have 10 criteria for which I want to do sensitivity analysis. I have used the AHP method to calculate the weights for each criterion. I am not sure how to perform sensitivity analysis for multiple ...
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Can a global sensitivity analysis be performed on Bayesian inference?

My question is, is it possible to perform a Global Sensitivity Analysis on a Bayesian inference model (not just on the prior, the entire model)? A bit of context: I am fairly new to Bayesian ...
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How to conduct sensitivity analysis on IPSW for survival data?

I am working on survival data, comparing two groups of patients (with or without treatment). These data have some selection bias, thus, I have chosen to weight my sample by Inverse Propensity Score ...
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How to interpret results a sensitivity analysis via G*Power

After reading several articles, e.g. from Daniel Lakens, Perugini etc., I performed sensitivity analysis. However, I think I understood how to interpret the sensitivity analysis if my observed effects ...
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Is there a method for Global Sensitivity Analysis that does not require special sampling methods?

I want to perform a global sensitivity analysis using randomly sampled data that already exists (or can be generated with only N randomized model runs). The impetus for this is to be able to use the ...
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Interpretation of the E-value for non-epidemiologists

A recent method for sensitivity analysis is the E-value (VanderWeele and Ping, 2017). Yet, I'm still struggling with the interpretation of such a value. Coming from outside of epidemiology, where risk ...
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Exclusion of participants based on sensitivity and criterion (SDT)

When I check the histogram of the participants' bias (measured by c), the distribution is right-skewed (i.e., more values are less than zero as expected). This indicates that the participants were ...
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Trade-off between omitting variables or dropping observations in multivariate logistic regression

Say you are selecting $n$ observations from a complex survey of $N$ individuals to create an analytical sample of relevant observations; and that you intend to fit a binomial multivariate logistic ...
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What-If Scenario Regression Modelling

I'm pondering a scenario involving some insurance data but this could be relevant in many fields. The idea is that I have a total count of some event. Let's imagine this count is the # of attorney ...
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what is the sensitivity of the neural network using standardized input

Suppose I trained a neural network with standardisation of the data following (X-EX)/std(X). The input is x(t) and output is y(t). How can I calculate the sensitivity of this trained network (...
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Can I perform sensitivity analysis, if I don't know expected prediction results?

Can I perform sensitivity analysis, if I don't know expected prediction results? I.e. I have a model with input parameters and weights. But I don't know when a prediction should be true and when false....
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How do you deal with A/B testing for small samples?

I am performing A/B testing (basically hypothesis testing) with relatively small samples, so the results are largely inconclusive. I am aware of techniques like CUPED (for decreasing the sample ...
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Difference-in-Difference regression model for sensitivity analysis

I have 5-year sales information from a grocery store in Canada. I want to check whether an event that happened in 2017, affected the effect of the price of a product on its sales. For example, imagine ...
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Estimating forecasting error in multi-step process

Suppose a process which looks something like this time series 1 --> model 1 --> time series 2 --> model 2 --> time series 3 An initial time series, which is a forecast, is used as input ...
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How many percentage to randomize and how many iterations in a "what-if analysis"?

I've got complete separated data as such: ...
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Sensitivity analysis after multiple imputation

After reviewing the literature there seems to be little consensus regarding the best way of performing sensitivity analysis following multiple imputation for missing values. However, the growing ...
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Using importance sampling for prior sensitivity analysis in Bayesian modeling

I read a section on Bayesian sensitivity analysis in the following book by Carlin and Louis (2009), 'Bayesian Methods for Data Analysis' (3rd ed.), CRC Press. The context is a sensitivity analysis of ...
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Sensitivity analysis using R's mice package with multiple missing variables

I am using mice to multiply impute data on a dataset with many variables with missing values. I followed this vignette to do a sensitivity analysis to understand how the imputations are influenced by ...
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Interpretation of regression coefficients after power transform (possibily with polynomial transform and PCA) [duplicate]

In general I standardize my features before regression by subtracting the mean and dividing by unit variance: $$ \hat{X} = \frac{X - \bar{X}}{Var(X)}$$ With this basic standardization, interpreting ...
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How to do ANOVA analysis for therapeutic biomarker screening for drug sensitivity

I am new to Bioinformatics. The graph below (from GDSC database) is to find therapeutic biomarker for drug sensitivity. I wonder how to do this kind of ANOVA analysis on my own so as to make this kind ...
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What is the name for this type of sensitivity measure in regression analysis?

I have a way of calculating sensitivity of a regression that is very useful for my particular domain, but I don't know what it is called. I would like a name for it so I can look up additional ...
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Metafor package: choice of moderator for bias correction

I am doing a 3-level meta-analysis using rma.mv() function. I found a thread about bias diagnostics with an advice to use "regression test for funnel plot ...
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What do the specific values of the Sobol' indices mean?

I understand that first order and total effect Sobol' indices demonstrate the relative importance of the input parameters on the output of a given model. My question is, do the specific values of each ...
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Bayes theorem calculation not giving proper result when calculating the positive predictive value

I have following data from experiment to assess accuracy of test in patients with and without disease: Where T stands for test and D stands for disease. I want to get probability of (D+|T+) with ...
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Intuition for Sobol Indices

I have recently been learning about Sobol indices and have found them quite informative. However, as I have explored them I have encoutnered situations where I have found them counter intuitive and in ...
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Local sensitivity analysis with exponential and uniform distributions as input

For my thesis I need to run a sensitivity analysis on the input factors for a supply chain model. I am supposed to change the mean and the standard deviation (sd) of all input factors respectively by ...
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Estimating parameters of Virial equation using Ordinary Least Squares

I tried to estimate the positive parameters $B$ and $C$ of the Virial equation $pV=\bar{n}(RT+Bp+Cp^2)$, where $\bar{n}=0.25, \, T=300, \, R=8.314$ with the data $$\begin{align} p &= (50,60,\...
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How to interpret sensitivity power analyses?

Journals and reviewers increasingly ask authors to systematically report sensitivity power analyses. I know that a sensitivity power analysis allows you to determine the minimum effect size that the ...
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What are the sensitivity analyses for propensity score matching-based estimation?

I'm interested in using Propensity Score Matching (PSM) to create matched control vs treatment sample and estimate the treatment effect. But the problem with PSM is that the sample is matched based on ...
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Standardized beta coefficients in nonlinear regression

In linear models $Y=X\beta+\epsilon$, where the errors $\epsilon_i\sim\text{Normal}(0,\sigma^2)$ are independent, the standardized beta coefficients are given by $$ \beta_i^*=\beta_i\frac{\sigma_{x_i}}...
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Probabilistic estimates of Kaplan-Meier curves using S(t) and std.err for each time point

I am working on a survival analysis where I am fitting different parametric models to survival data. Varying the models that I have fit to the data is straightforward, via Cholesky decompositions- but ...
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Can first order sensitivity indices be greater than the total order sensitivity indices?

I am using variance based sensitivity analysis method from SAFE toolbox in matlab to determine the first order (Si) and total order sensitivity indices (STi). Theoretically, the STi is either equal to ...
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Sensitivity analysis cookbook

Suppose you are asked to replicate a paper and to perform a sensisitivity analysis. Where would you start from? The paper is in Economics so the point is to replicate main tables (multivariate ...
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How to interpret the result from local sensitivity analysis?

I am currently doing local sensitivity analysis on a model that has 40 input parameters. I varied the base case value by 10% within the range of [-1, 1]. While doing so the average change (here, I ...
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How to use sobol2002 for sensitivity analysis in R?

I have a very basic understanding of R and stat so my question may sound very simple. I am trying to do a sensitivity analysis on a model that takes 30+ input parameters. The model is created in R. ...
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What does it mean if the Sobol main and total effects indices are the same?

What does it mean when the total and main effects ANOVA indices are the same? Does it mean there is zero interaction of the different inputs? Is there some other way to quantify or understand that? I ...
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sensitivity analysis without model

Perhaps I should call it input-output correlation test, and the tricky part is no model exists between those inputs and outputs. The basic idea is there are many inputs and one output, and I would ...
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Individual significance of data points in correlation

In this question on stackoverflow, I asked about how it is possible to find the individual significance of each correlation coefficient of each node. I answered the question myself later stating that ...
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Sensitivity rates where TP =0 and FN =0

In calculating sensitivity rates where TP =0 and FN =0 and the formula is TP/(TP+FN) - although it mathematically won't compute, does this equate to 100% sensitivity since it has correctly identified ...
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Sensitivity Analysis with categorical predictive variables in R

I am doing a project where I have to predict the Sales Units in fashion and intend to run a Random Forest, Neural Networks, and Support Vector Machine models. However, my predictive variables are all ...
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Which approach should be used to compare two different measurement techniques of same samples?

I have individually measured failure forces of 8 materials and those recorded with A method and B method in same time: 8 results in each method, A=8 and B=8. The range of data of both measurement ...
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Sensitivity of regression parameters to noise

How sensitive are the parameters obtained from OLS, logistic or other regression methods to noise ? By noise, I mean minor changes. For e.g. adding a small noise $-1<\Delta<1$ to $\beta_1$ in $...
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Analyse sensitivity of hyper-parameters of Machine Learning Models

I want to analyse how sensitive my non neural net machine learning models are to the choice of the different parameters. I am currently using grid search to tune the models. Is there any method that I ...
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Global sensitivity Morris method - choice of delta and normalisation of the elementary effects

I have few questions regarding the Morris method (as decribed e.g. in Campolongo, Cariboni, Saltelli, Environmental Modelling & Software 22, 2007 or Wenthworth et al. J. Uncertainty Quantification ...
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